text: from data_key_points import load_test
  from train_key_points import get_model, preprocess, batch_size, input_shape
  from constants import key_points_desired_size
  from skimage.io import imsave, imread, imshow
  import numpy as np
  from matplotlib import pyplot as plt
  
  imgs, ids = load_test()
  print(imgs.shape)
  imgs = preprocess(imgs)
  print(imgs.shape)
  
  print('-'*30)
  print('Loading saved weights...')
  print('-'*30)
  model = get_model(input_shape)
  model.load_weights('model_kp.h5')
  
  print('-'*30)
  print('Predicting key points on test data...')
  print('-'*30)
  kps = model.predict(imgs, verbose=1, batch_size=batch_size)
  for kp in kps:
  	kp *= 16.0
  	pass
  
  np.save('kp_resutl.npy', kps)
  
  # i = 0
  # for image, image_id in zip(imgs, ids):
  # 	image = (image[:, :, 0])
  # 	kp = kps[i]
  # 	kp *= 16
  
  # 	middle = (kp[0], kp[1])
  # 	thumb = (kp[2], kp[3])
  # 	center = (kp[4], kp[5])
  # 	i += 1
  